The impact of environmental regulations on the performance of regional collaborative innovation-in case of China's 30 provinces.

With rapid economic growth in the twenty-first century, innovation has become an essential component of national development, and industry-university-research regional collaborative innovation is the key to implementing China's innovation plan. Using panel data from 30 provinces and cities in China (excluding Tibet Autonomous Region) from 2011 to 2018, this paper employs the two-stage dynamic DEA model to develop a rating index system of regional collaborative innovation performance, which is divided into knowledge innovation stage and technology innovation stage, and measures the collaborative innovation efficiency of 30 provinces in China. The environmental regulation score is then determined by using the entropy method. Finally, an experimental application of the panel Tobit model is conducted to investigate the impact mechanism of environmental regulation on regional collaborative innovation. The results reveal that the collaborative innovation efficiency values of the majority of provinces are between 0.5 and 0.7, leaving ample room for growth. When the efficiency value of collaborative innovation is broken down by region, the eastern, central, and western regions show a pattern of "rising in the east, stable in the center, and falling in the west." The findings of the Tobit regression reveal that the effect of environmental regulation on regional collaborative innovation performance follows a "U"-shaped distribution, confirming the "Porter Hypothesis." This study proposes remedies and proposals to enhance regional collaborative innovation performance from the perspective of environmental regulation.

Linkage analysis of water resources, wastewater pollution, and health for regional sustainable development-using undesirable three-stage dynamic data envelopment analysis.

With the development of China's economy, pollution has made serious impact on environment and human health. However, environmental protection and residents' health are becoming more and more important along with the country's social and economic transformation. Most existing studies have analyzed the path of economic impact on the environment and the production, pollution, and health in isolation. This research takes panel data of 30 provinces in China (including autonomous regions and municipalities, excluding Tibet, Hong Kong, Macau, and Taiwan) spanning 2014 to 2017 as an example, builds an evaluation indicator system on the basis of the three stages of economic production, wastewater treatment, and human health, and uses the undesirable three-stage dynamic data envelopment analysis model to empirically evaluate the total efficiency, stage efficiency, and the efficiency of various indicators. The research results show the average efficiency of the three stages in most provinces in four years is below 0.5, indicating the poor coordination of each stage; the efficiency gaps among the eastern, central, and western regions are very large because of the resource endowments, geographical environment, industrial structure, strategic adjustment, and other infactors. The total efficiency of the three stages of production input, wastewater treatment, and health output in the eastern region are higher than that of the central region and the western region. From the perspective of stage efficiency, most of the 30 provinces exhibit production efficiency < health efficiency < wastewater treatment efficiency. For the three-phase input and output indicators, the efficiency values and development trends of different provinces vary. The efficiencies of input variables in the wastewater treatment stage and health stage are low in most provinces. This means that the provinces should implement accurate policies according to their own evaluation results and improve the relevance and coordination among the three stages through reasonable allocation of medical input and arrangement of urban employment.

Climate Change Impacts on Agricultural Production and Crop Disaster Area in China.

As one of the largest agricultural countries in the world, China has always paid close attention to the sustainable development of agricultural production efficiency. However, with global climate change, extreme weather has become an exogenous factor that cannot be ignored, as it affects agricultural production. Most of the existing studies only consider the domestic natural resources and economic factors, without fully considering the external climate factors. This paper uses the super undesirable dynamic Slacks-Based Measures (SBM) under an exogenous variable model to simulate the external environmental factors by adding extreme weather days. The Dagum Gini coefficient and kernel density estimation are used to explore the regional differences in agricultural production in China. The results show that the agricultural production efficiency is higher in the eastern region, and the difference in agricultural production efficiency among the provinces in the middle and western regions is large, showing a trend of polarization. The difference in the Gini coefficient between the middle and western regions is more significant. The main contribution factor of the Dagum Gini coefficient is the inter-regional difference. The regional concentration degree of agriculture in China is decreasing, the regional distribution of agricultural water resources is more balanced, and the national regional difference gradually decreases. Finally, some suggestions are put forward, such as extreme weather control, agricultural water supply, and water-saving measures.

Comparing Economics, Environmental Pollution and Health Efficiency in China.

As the modern economy develops rapidly, environmental pollution and human health have also been threatened. In recent years, relevant research has focused on subjects such as energy and economic, environmental pollution and health issues. Yet this has not considered the use of water resources and the impact of wastewater pollutant emissions on the economy and health. This article has combined the following factors like water consumption with wastewater discharge, pollutant concentration in sewage and local medical care expenditure and put them into the model of water resources, energy and health measurement, and a two-stage dynamic data envelopment analysis (DEA) model considering undesirable outputs is applied to 30 provinces (including autonomous regions and municipalities) to calculate the total efficiency, production efficiency and health efficiency in 2014-2017.The results show that the total efficiency values of most provinces are between 0.2 and 0.4, providing large room for improvement. Production efficiency and health efficiency have increased in recent years, but the health efficiency values of most provinces are still so low that they have dragged back the overall efficiency. The key impact indicators of different provinces are different, and each province should formulate different policies according to its own specific conditions so as to purposefully to deepen the energy, economic and medical reforms in each province, and also to promote sustainable economic development while improving health efficiency.